Autonomous ultrasound-guided tissue dissection

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Abstract

Intraoperative ultrasound imaging can act as a valuable guide during minimally invasive tumour resection. However, contemporaneous bimanual manipulation of the transducer and cutting instrument presents significant challenges for the surgeon. Both cannot occupy the same physical location, and so a carefully coordinated relative motion is required. Using robotic partial nephrectomy as an index procedure, and employing PVA cryogel tissue phantoms in a reduced dimensionality setting, this study sets out to achieve autonomous tissue dissection with a high velocity waterjet under ultrasound guidance. The open-source da Vinci Research Kit (DVRK) provides the foundation for a novel multimodal visual servoing approach, based on the simultaneous processing and analysis of endoscopic and ultrasound images. Following an accurate and robust Jacobian estimation procedure, dissections are performed with specified theoretical tumour margin distances. The resulting margins, with a mean difference of 0.77mm, indicate that the overall system performs accurately, and that future generalisation to 3D tumour and organ surface morphologies is warranted.

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Pratt, P., Hughes-Hallett, A., Zhang, L., Patel, N., Mayer, E., Darzi, A., & Yang, G. Z. (2015). Autonomous ultrasound-guided tissue dissection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9349, pp. 249–257). Springer Verlag. https://doi.org/10.1007/978-3-319-24553-9_31

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